Robots enhance the predictability and accuracy of manufacturing processes, by reliably and repeatedly performing work upon parts (e.g., composite carbon fiber parts, steel parts, etc.) via an end effector in order to drill holes, place rivets, etc. This enhanced predictability helps to ensure that the fabrication of complex parts is performed in an expected manner and without undesirable out-of-tolerance inconsistencies.
While robots are effective tools for performing work upon complex parts consistently, the training process for robots may be time-consuming and expensive. Robots are often governed by Numerical Control (NC) programs, which guide the actions of the robot to move an end effector of the robot to a desired location, in order to perform work upon a part via the end effector as desired.
Even an NC program that is theoretically perfect is subject to error when implemented in a real-world scenario. For example, forces applied by a dressing (e.g., cabling, etc.) for the robot may cause the robot to be subject to minor errors in movement when the robot is actuated. Similarly, if the NC program quickly changes the speed of the robot, positional error may accrue as acceleration and deceleration apply unexpected forces to the frame of the robot. For these and other reasons, it is not uncommon for experts training a robot to direct the robot to perform work upon multiple parts as part of a training process. The parts are disposed after they are worked upon by the robot, and errors in the location of work performed upon the parts is then detected by an operator and utilized to modify the NC program. Accordingly, those skilled in the art continue with research and development efforts in the field of robotic fabrication.